Artificial Intelligence-Based Text-To-Speech System and Method

2. The TTS system of claim 1 wherein the operations further comprise converting a frequency domain signal combined from a neural network and the pre-existing knowledgebase into the corrected speech signal.

3. The TTS system of claim 1 wherein the data in the pre-existing knowledgebase of phonemes comprises average basic acoustic signal data of how a speaker speaks derived from the recorded audible speech.

4. The TTS system of claim 1 wherein the operations further comprise correcting for psychoacoustic perceived speech signal distortions of the pre-existing knowledgebase of phonemes.

5. The TTS system of claim 1 wherein the operations further comprise upsampling a frequency of an input vector to another frequency of an intermediate vector.

6. The TTS system of claim 5, wherein the input vector comprises at least one of a base frequency, a phoneme duration, and a phoneme sequence.

7. The TTS system of claim 1 wherein the operations further comprise correcting voiced phonemes of the pre-existing knowledgebase of phonemes.

8. The TTS system of claim 1 wherein the operations further comprise correcting unvoiced phonemes of the pre-existing knowledgebase of phonemes.

9. The TTS system of claim 1 wherein a neural network is configured based on psychoacoustic modeling of phonemes.

11. The method of claim 10 wherein the operations further comprise converting a frequency domain signal combined from a neural network and the pre-existing knowledgebase into the corrected speech signal.

12. The method of claim 10 wherein the data in the pre-existing knowledgebase of phonemes comprises average basic acoustic signal data of how a speaker speaks derived from the recorded audible speech.

13. The method of claim 10 wherein the operations further comprise correcting for psychoacoustic perceived speech signal distortions of the pre-existing knowledgebase of phonemes.

14. The method of claim 10 wherein the operations further comprise upsampling a frequency of an input vector to another frequency of an intermediate vector.

15. The method of claim 14, wherein the input vector comprises at least one of a base frequency, a phoneme duration, and a phoneme sequence.

16. The method of claim 10 wherein the operations further comprise correcting voiced phonemes of the pre-existing knowledgebase of phonemes.

17. The method of claim 10 wherein the operations further comprise correcting unvoiced phonemes of the pre-existing knowledgebase of phonemes.

18. The method of claim 10 wherein a neural network is configured based on psychoacoustic modeling of phonemes.

20. The non-transitory computer-readable medium of claim 19 wherein the operations further comprise correcting for psychoacoustic perceived speech signal distortions of the pre-existing knowledgebase of phonemes.